A three-dimensional computational model for inlet distortion in fan and compressor

Guo, Jin; Hu, Jun

doi:10.1177/0957650917719811

Cited by 16 publications

(10 citation statements)

References 28 publications

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“…The modeling methods of the blade source terms are based on the work of Guo and Hu. 11 For completeness and clarity, the theoretical explanations of the body force model are reorganized and enriched here.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…Body force model, also known as the immersed boundary method with smeared geometry (IBMSG), 7 has generated considerable recent research interest. 8–15 The basic principle of this kind of model is that source terms are added to 3D unsteady flow equations to simulate flow turning, pressure rise, and loss effects across blade rows, which allows a regular coarse grid. Thus, the 3D body force model, a trade-off between the calculated accuracy and the computational costs, has the potential to predict the combined effects of complex distortion on compressors.…”

Section: Introductionmentioning

confidence: 99%

“…The aim of this study is to propose a mixed-fidelity computational model for complex inlet distortion in aero engines under the guidance of the numerical zooming technique. In the present model, the compression system of the engine is modeled by a 3D body force model established by Guo and Hu 11 and the remaining components are still solved through the method of a 2D parallel engine model developed in Nanjing University of Aeronautics and Astronautics. 21 The approach can be utilized to quantify the compressor tolerance to complex inlet distortion in the whole engine environment as well as the effect of inlet distortion on the engine overall performance in an efficient and time-saving manner.…”

Section: Introductionmentioning

confidence: 99%

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A mixed-fidelity computational model of aero engine for inlet distortion

Guo

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper presents a mixed-fidelity model to investigate the effect of complex inlet distortion on aero gas turbine engines. The approach is developed by integrating a three-dimensional body force model of multistage compressors and a classical two-dimensional parallel engine model. The internal flow field of a high bypass ratio turbofan engine under different forms of total pressure distortion is simulated by the model. The simulations are discussed in depth to reveal the features of the distorted flow field in the compression components under the whole engine environment. The relationship between the overall performance of the engine and the intensity of inlet total pressure distortion is investigated quantitatively. It is evident that the mixed-fidelity model has the capability to quantitatively evaluate the effect of complex inlet distortion on the performance and the internal flow field of engines with low computational costs.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A mixed-fidelity computational model of aero engine for inlet distortion

Guo

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…In terms of loss models, there has also been some progress. Guo and Hu in 2017 [13] presented a simplified analytical loss coefficient which yields the entropy generation along the streamline. That loss model is an empirical correlation and is derived for National Advisory Committee for Aeronautics (NACA) blades.…”

Section: Introductionmentioning

confidence: 99%

A New Loss Generation Body Force Model for Fan/Compressor Blade Rows: An Artificial-Neural-Network Based Methodology

Pazireh

Defoe

2021

IJTPP

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Body force models of fans and compressors are widely employed for predicting performance due to the reduction in computational cost associated with their use, particularly in nonuniform inflows. Such models are generally divided into a portion responsible for flow turning and another for loss generation. Recently, accurate, uncalibrated turning force models have been developed, but accurate loss generation models have typically required calibration against higher fidelity computations (especially when flow separation occurs). In this paper, a blade profile loss model is introduced which requires the trailing edge boundary layer momentum thicknesses. To estimate the momentum thickness for a given blade section, an artificial neural network is trained using over 400,000 combinations of blade section shape and flow conditions. A blade-to-blade flow field solver is used to generate the training data. The model obtained depends only on blade geometry information and the local flow conditions, making its implementation in a typical computational fluid dynamics framework straightforward. We show good agreement in the prediction of profile loss for 2D cascades both on and off design in the defined ranges for the neural network training.

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“…Among different types of inlet distortions, the total pressure distortion is one of the most common forms compressor theory (Mazzawy, 1977;Pearson & McKenzie, 1959), actuator disks (Hawthorne et al, 1978;Horlock, 1979), simple semi-empirical methods (Valencia et al, 2017), through-flow analysis (Hall et al, 2017) and body force methods (Guo & Hu, 2018;Thollet et al, 2016). Although these methodologies can get the features of non-uniform inflow redistributions across the rotor through low computational cost, many flow details such as the secondary flows in compressors can't be well and fully captured due to the corresponding assumptions and simplifications.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a transonic axial-flow compressor under inlet total pressure distortion to enhance aerodynamic performance

Yang

et al. 2020

Engineering Applications of Computational Fluid Mechanics

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In a boundary layer ingestion (BLI) propulsion system, the compressor rotor operates under the condition of a severe inflow distortion because the boundary layers on the surface of aircraft have been ingested. In this situation, the low-momentum fluid would inevitably raise the blade load and aggravate the local aerodynamic losses, thus severely deteriorating the compressor overall aerodynamic performance. The paper has applied a sweep optimization design based on surrogate model and genetic algorithm to a transonic axial-flow compressor at the condition of total pressure distorted inflow. The optimization objective is to improve the compressor efficiency. The sweep design has been implemented through controlling the shape of the blade stacking line and the time-saving steady numerical simulations are mainly utilized in the optimization process. Then, the full-annulus unsteady CFD calculations have been conducted for validating the optimized design and further analyzing the flow mechanisms of performance improvements. The computational results show that the inflow distortion has led to non-uniform distributions of the tip leakage loss and the hub flow separation loss along the circumferential direction. It is found that the rotor blade has suffered from the highest tip leakage losses and hub separation losses during the blade leaving the distorted region. After rotor sweep optimization, both tip leakage and hub separation losses have been notably reduced along the full circumferential direction. Moreover, for different pitchwise locations, the optimized rotor sweep design has achieved more aerodynamic performance improvements in the process of the rotor blade leaving the distorted region than those in the processes of the rotor blade moving out of, moving towards and entering the distorted region. Overall, the optimized design performs better than the baseline design in terms of adiabatic efficiency in the entire operating range. In the meanwhile, the total pressure ratio has been maintained. Specifically, an approximately 0.5% increment of efficiency has been achieved by the optimized design at the optimization point. For this paper, the major purpose is to offer useful guidelines for fan/compressor design strategy to achieve high aerodynamic performances under distorted inflow working condition.

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A three-dimensional computational model for inlet distortion in fan and compressor

Cited by 16 publications

References 28 publications

A mixed-fidelity computational model of aero engine for inlet distortion

A mixed-fidelity computational model of aero engine for inlet distortion

A New Loss Generation Body Force Model for Fan/Compressor Blade Rows: An Artificial-Neural-Network Based Methodology

Optimization of a transonic axial-flow compressor under inlet total pressure distortion to enhance aerodynamic performance

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